IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
21-23 October 2019 // Beijing, China

Tutorials

Monday, 21 October 2019, 14:00-15:30

TUT-1: EPR: Electric Power System Resilience

Monday, 21 October 2019, 16:00-17:30

TUT-2: PQA: Power Quality Analysis in Power Grids with a High Share of Power Electronics based Generation and Load

Tuesday, 22 October 2019, 09:00-10:30

TUT-3: MBP: Machine Learning and Big Data Analytics in Power Distribution Systems

Tuesday, 22 October 2019, 16:00-17:30

TUT-4: BSE: Blockchain for Smart Energy Systems


TUT-1: EPR: Electric Power System Resilience

Date: Monday, 21 October 2019
Time: 14:00-15:30
Location: Room 1
Presenters: Chen Chen, Dong (Kevin) Jin

One of the ultimate goals of electric power systems is to “Keep the Light On”; however, ensuring an uninterrupted electricity supply is challenging for such a complex engineering network exposed to various threats. While for decades electric power systems have been designed to possess high levels of reliability to withstand typical threats, that is, N-1 security criterion, recent catastrophic power outages caused by extreme events have highlighted the importance and urgency of enhancing resilience of power system infrastructure. These extreme events consist of natural disasters (e.g., Hurricane Sandy of 2012), man-made errors (e.g., Northeast blackout of 2003), and even ever-growing cyber incidents (e.g., Ukraine power grid cyberattack of 2015). To achieve a resilient electric power system, various technical challenges need to be addressed spanning from planning to operation, and involving investment, preparation, prevention, response, mitigation, and recovery. Multidisciplinary fields (e.g., power engineering, operation research, data analytics, computer science, transportation, telecommunications, etc.) play an essential to facilitate this target.

This tutorial aims to provide the audience a better understanding of electric power grid resilience, including why the grid resilience is important, how to quantify the resilience, methods to enhance grid resilience from long-term planning, pre-event preparation, and post-event restoration stages, and how the grid modernization plays an important role. In addition, the tutorial will also specifically discuss how the distributed energy resources and microgrids help to facilitate grid resilience with some examples and case studies. The tutorial will also cover the cybersecurity issues in modern electric power systems as they increasingly adopt advanced information technology to boost control efficiency, which unfortunately opens up a new front for a potential “cyber Pearl Harbor” as well as methodologies targeting a variety of security solutions at different layers, i.e., communication network, control application, and measurement device layers. The challenges and future direction will be discussed in the end. Through this tutorial, the audience can learn both basic knowledge of grid resilience and the cutting-edge R&D in this area.

Biography

Dr. Chen Chen is an Energy Systems Scientist at Argonne National Laboratory, covers the introduction of electric power system resilience, resilience quantification and measures to enhance resilience, and utilizing distributed energy resources and microgrids for resilience enhancement. He is the chair for Special Interest Group of Cyber Security, Privacy, and Resilience for the Smart Grid in IEEE Communications Society Smart Grid Communications Emerging Technical Committee. He received the Ph.D. in electrical engineering from Lehigh University in 2013. He has authored and co-authored more than 50 journals and conference publications in the area of smart grid. He has been serving as an editor of IEEE Transactions on Smart Grid since 2015, and served as a symposium co-chair for IEEE SmartGridComm2015, Symposium on Data Management, Grid Analytics, and Dynamic Pricing. He is the recipient of the IEEE Power and Energy Society Chicago Chapter Outstanding Engineer Award in 2018. More information can be found at http://www.morningchen.net

Dong (Kevin) Jin is an Assistant Professor in the Computer Science Department at the Illinois Institute of Technology. He obtained his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2013. His research interests include smart grid security, cyber-security, simulation modeling and analysis, software-defined networking. He is a recipient of the Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) award. He also received the best paper awards at the ACM SIGSIM Conference on Principles of Advanced and Distributed Simulation (PADS) in 2012 and 2015. More information can be found at http://cs.iit.edu/~djin/

 

TUT-2: PQA: Power Quality Analysis in Power Grids with a High Share of Power Electronics based Generation and Load

Date: Monday, 21 October 2019
Time: 16:00-17:30
Location: Room 1
Presenters: Gerd Bumiller, Lijun Cai, Jan-Philipp Kitzig

The analysis of Power Quality (PQ) in the power grid will face new challenges in the future. PQ is a collective term for several physical quantities such as

  • Root-Mean-Square value of voltage and current
  • Mains frequency
  • Flicker
  • Symmetry in three-phase systems
  • Spectral Composition (harmonics, Power line communication signals, etc.)
  • Voltage transients
  • (Harmonic) impedance

A wide range of different measurement approaches and devices exists to gather and measure those quantities in different parts and levels of the grid in order to enable system operators to control power flows, to keep the grid stable (reactive power, voltage levels, resonances) and to provide accurate accounting to their customers.

In the first part of this tutorial, the state of the art in PQ measurement will be presented. Different measurement devices and their importance for the grid operation such as PQ meters and Phasor Measurement Units (PMUs) are presented and their principle of function will be explained.

Subsequently, problematic distorting effects and inaccuracies of these devices will be revealed with regard to the ongoing transformation of the power system towards more inverter based generation and load as well as a decreasing share of directly connected synchronous machines. As an example, the increasing volatility of the mains frequency and its influence on spectral analysis will be mentioned; especially when it comes to the determination of power flows on harmonics. The accurate determination of the harmonic’s phase is crucial for the power flow determination, but it is highly prone to spectral leakage in the event of a mains frequency transient or off-nominal mains frequency.

The second part of the tutorial will state the current developments in science and industry, which aim at attenuating those effects. Fast and precise mains frequency measurement and the estimation of the Rate of Change of Frequency (RoCoF) gain in importance. Several new approaches to mains frequency measurement will be presented, including new PMU algorithms as well as algorithms based on Phase-Locked-Loops (PLL). Thereafter, a new Power Quality Measurement System concept will be introduced, which merges the advantages of PMUs and PQ-meters to provide mains frequency synchronous sampling of current and voltage at a rate of exactly 215 samples per period. Since this is the work of the lecturers Bumiller and Kitzig, the concept is compared with the work of other scientists and critically placed in the current scientific context. A wide range of different measurement approaches and devices exists to gather and measure those quantities in different parts and levels of the grid in order to enable system operators to control power flows, to keep the grid stable (reactive power, voltage levels, resonances) and to provide accurate accounting to their customers.

The importance of PQ analysis and the need to improve current technology will then be demonstrated using a practical example by Prof. Li-Jun Cai. At first, an introduction to harmonic resonance analysis for power systems with large integration of renewable energies will be given. Thereafter, the harmonic impedance analysis of renewable energy sources such as doubly fed induction generators (DFIGs), full converters (FC) wind turbines or photovoltaic (PV) will be examined, followed by the harmonic impedance analysis of total wind farms and PV parks. At the end, the general methods for resonance damping control will be introduced shortly.

Biography

Prof. Dr. Gerd Bumiller received the Dipl.Univ. and Ph.D. degrees in electrical engineering from the University of Erlangen–Nuremberg, Erlangen, Germany, in 1997 and 2009, respectively.

From 1997 to 2011, he was with iAd GmbH, Germany, where he was involved in development, project, and research achievement as well as technological responsibility for all power line communication products. Since 2011, he has been a Professor in energy and information engineering with the Institute of Computer Science, University of Applied Sciences Ruhr West, Bottrop, Germany.

Dr. Bumiller serve as Chair of Power Line Communications Technical Committee of the IEEE Communication Society since 2018.

Prof. Dr. Lijun Cai received his PhD in electrical engineering in 2004 from the University of Duisburg-Essen, Germany. His research focused on the optimal location and multi-objective coordinated control of FACTS devices, power system oscillation damping controller design, power system economics.

From 2004 to 2006, he worked as a post doctorial fellow in University of Duisburg-Essen, Germany. His research focused on the dynamic voltage stability analysis and control in large power systems, doubly-fed induction generator controller design.

From 2006 to 2009, he was with Vattenfall Europe Transmission (TSO), Germany. He was responsible for the static and dynamic European power system study and integration analyses of large wind power plants.

From 2009 to 2015, he was the head and leading expert of the department for wind turbine modelling, grid connection and simulation, REpower System AG. He was responsible for the wind turbine aerodynamic, mechanic and electrical system (EMT and RMS) modelling, wind turbine and wind power plant control, grid connection and simulation of large wind power plants.

From 2015 to 2017, he was chief scientist with Global Energy Interconnector Research Institute (GEIRI) Berlin. He was responsible for building and heading the department: HVDC and New Power System Technology. Also was responsible for coordinating and supervising of the research projects with different companies, universities and research institutes.

From 2018, he is the University Professor with University of Rostock. His research interest focus on: large power system static analyses, large power system dynamic stability analysis and control, renewable energy generations, LCC- and VSC-HVDC system analyses and design, large scale energy storage systems such as doubly fed induction generators (DFIGs), full converters (FC) wind turbines or photovoltaic (PV) will be examined, followed by the harmonic impedance analysis of total wind farms and PV parks. At the end, the general methods for resonance damping control will be introduced shortly.

Dipl. Ing. Jan-Philipp Kitzig received the M.Eng. degree in mechanical engineering from Hochschule für Technik und Wirtschaft des Saarlandes, University of Applied Sciences, Saarbrücken, Germany, in 2015. In 2016, he joined the University of Applied Sciences Ruhr West, Bottrop, Germany, as an Assistant Researcher with Prof. Bumiller, where he was involved in power systems engineering. His current research interests include measurement technologies, digital signal processing, power quality, and phasor measurement.

 

TUT-3: MBP: Machine Learning and Big Data Analytics in Power Distribution Systems

Date: Tuesday, 22 October 2019
Time: 09:00-10:30
Location: Room 1
Presenter: Nanpeng Yu

This tutorial covers the applications of machine learning and big data analytics in electric power distribution systems. The value, velocity, volume, and variety of big data in power distribution systems will be discussed. The tutorial will briefly review the basics of unsupervised, supervised, and reinforcement-learning algorithms. A few important data-driven applications in electric power distribution systems will be presented. These applications include 1) Distribution system topology identification; 2) Anomaly detection in power distribution systems; 3) Spatial-temporal load and DER forecasting; 4) Predictive maintenance of distribution system equipment, and 5) Reinforcement Learning based Control in Power Distribution Systems.

Biography

Prof. Nanpeng Yu (IEEE SM’16) received his Ph.D. degree in electrical engineering from Iowa State university in 2010. Dr. Yu was a senior power system planner and project manager at Southern California Edison from 2011 to 2014. Currently, Professor Yu is the director of Smart Grid Innovation Laboratory of the Electrical and Computer Engineering department at University of California, Dr. Yu is the recipient of the Regents Faculty Fellowship and Regents Faculty Development award from University of California. His received a best paper award from the Second International Conference on Green Communications, Computing and Technologies and three best paper finalist awards from IEEE Power and Energy Society General Meeting. Dr. Yu is co-chair for IEEE Big Data Applications in Power Distribution Networks Task Force and secretary of the power system planning and operations subcommittee. Dr. Yu currently serves as the associate editor for IEEE Transactions on Smart Grid and International Transactions on Electrical Energy Systems.

 

TUT-4: BSE: Blockchain for Smart Energy Systems

Date: Tuesday, 22 October 2019
Time: 16:00-17:30
Location: Room 1
Presenter: Yan Zhang

Smart power grid is a modernized grid that proactively uses state-of-the-art technologies in the areas of sensing, communications, control, and computing technology to dramatically improve efficiency, sustainability, stability, and security. With the development of the distributed microgrid architecture, renewable energy resources and widespread electric vehicles, smart grid is facing many unprecedented challenges for the smart energy management and operation.

In this tutorial, we will mainly focus on Blockchain technology and application for smart energy systems. We will first introduce the key concepts, challenges and visions in the future generation smart grid. We also present the scenarios on exploring Internet principles (e.g., Peer-to-Peer) in the energy domain for energy sharing and trading. Then, we will introduce Blockchain technology and its general applications, as well as new applications in the energy domain. Next, we will present Blockchain for smart energy management in decentralized Peer-to-Peer (P2P) energy sharing and Vehicle-to-Grid scenarios. Auction theory and game theory will be also explored for energy balance and protecting users’ private information. In addition, combining blockchain and edge computing will be explored. Finally, we will conclude and point out related open issues.

Biography

Professor Yan Zhang is Full Professor at University of Oslo, Norway. He is a highly cited researcher and a IET Fellow. He is also the chair of IEEE Technical Committee on Green Communications & Computing and IEEE VTS distinguished lecturer.

He received a PhD degree in School of Electrical & Electronics Engineering, Nanyang Technological University, Singapore. He is an associate editor or on the editorial board of a number of well-established scientific international journals. He serves as organizing committee chairs and technical program committee for many international conferences. His current research interests include: wireless networks leading to 5G Beyond and 6G, and cyber-physical systems (e.g., smart grid, healthcare, transport).